{"title":"虚拟临床试验揭示靶向肿瘤相关巨噬细胞和小胶质细胞治疗胶质母细胞瘤的重要临床潜力。","authors":"Blanche Mongeon, Morgan Craig","doi":"10.1002/psp4.70033","DOIUrl":null,"url":null,"abstract":"<p><p>Glioblastoma is the most aggressive primary brain tumor, with a median survival of 15 months with treatment. Standard-of-care (SOC) consists of resection, radio- and chemotherapy. Clinical trials involving PD-1 inhibition with nivolumab combined with SOC failed to increase survival. A quantitative understanding of the interactions between the tumor and its immune environment that drive treatment outcomes is currently lacking. As such, we developed a mathematical model of tumor growth that considers CD8+ T cells, pro- and antitumoral tumor-associated macrophages and microglia (TAMs), SOC, and nivolumab. Using our model, we studied five TAM-targeting strategies currently under investigation for solid tumors. Our results show that PD-1 inhibition fails due to a lack of CD8+ T cell recruitment during treatment, explained by TAM-driven immunosuppressive mechanisms. Our model predicts that while reducing TAM numbers does not improve prognosis, altering their functions to counter their protumoral properties has the potential to considerably reduce post-treatment tumor burden. In particular, restoring antitumoral TAM phagocytic activity through anti-CD47 treatment in combination with SOC was predicted to nearly eradicate the tumor. By studying time-varying efficacy with the same half-life as the anti-CD47 antibody Hu5F9-G4, our model predicts that repeated dosing of anti-CD47 provides sustained control of tumor growth. We propose that targeting TAMs by enhancing their antitumoral properties is a highly promising avenue to treat glioblastoma and warrants future clinical development. Together, our results provide proof-of-concept that mechanistic mathematical modeling can uncover the mechanisms driving treatment outcomes and explore the potential of novel treatment strategies for hard-to-treat tumors like glioblastoma.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":" ","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Virtual Clinical Trial Reveals Significant Clinical Potential of Targeting Tumor-Associated Macrophages and Microglia to Treat Glioblastoma.\",\"authors\":\"Blanche Mongeon, Morgan Craig\",\"doi\":\"10.1002/psp4.70033\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Glioblastoma is the most aggressive primary brain tumor, with a median survival of 15 months with treatment. Standard-of-care (SOC) consists of resection, radio- and chemotherapy. Clinical trials involving PD-1 inhibition with nivolumab combined with SOC failed to increase survival. A quantitative understanding of the interactions between the tumor and its immune environment that drive treatment outcomes is currently lacking. As such, we developed a mathematical model of tumor growth that considers CD8+ T cells, pro- and antitumoral tumor-associated macrophages and microglia (TAMs), SOC, and nivolumab. Using our model, we studied five TAM-targeting strategies currently under investigation for solid tumors. Our results show that PD-1 inhibition fails due to a lack of CD8+ T cell recruitment during treatment, explained by TAM-driven immunosuppressive mechanisms. Our model predicts that while reducing TAM numbers does not improve prognosis, altering their functions to counter their protumoral properties has the potential to considerably reduce post-treatment tumor burden. In particular, restoring antitumoral TAM phagocytic activity through anti-CD47 treatment in combination with SOC was predicted to nearly eradicate the tumor. By studying time-varying efficacy with the same half-life as the anti-CD47 antibody Hu5F9-G4, our model predicts that repeated dosing of anti-CD47 provides sustained control of tumor growth. We propose that targeting TAMs by enhancing their antitumoral properties is a highly promising avenue to treat glioblastoma and warrants future clinical development. Together, our results provide proof-of-concept that mechanistic mathematical modeling can uncover the mechanisms driving treatment outcomes and explore the potential of novel treatment strategies for hard-to-treat tumors like glioblastoma.</p>\",\"PeriodicalId\":10774,\"journal\":{\"name\":\"CPT: Pharmacometrics & Systems Pharmacology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2025-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CPT: Pharmacometrics & Systems Pharmacology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1002/psp4.70033\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PHARMACOLOGY & PHARMACY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"CPT: Pharmacometrics & Systems Pharmacology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/psp4.70033","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
Virtual Clinical Trial Reveals Significant Clinical Potential of Targeting Tumor-Associated Macrophages and Microglia to Treat Glioblastoma.
Glioblastoma is the most aggressive primary brain tumor, with a median survival of 15 months with treatment. Standard-of-care (SOC) consists of resection, radio- and chemotherapy. Clinical trials involving PD-1 inhibition with nivolumab combined with SOC failed to increase survival. A quantitative understanding of the interactions between the tumor and its immune environment that drive treatment outcomes is currently lacking. As such, we developed a mathematical model of tumor growth that considers CD8+ T cells, pro- and antitumoral tumor-associated macrophages and microglia (TAMs), SOC, and nivolumab. Using our model, we studied five TAM-targeting strategies currently under investigation for solid tumors. Our results show that PD-1 inhibition fails due to a lack of CD8+ T cell recruitment during treatment, explained by TAM-driven immunosuppressive mechanisms. Our model predicts that while reducing TAM numbers does not improve prognosis, altering their functions to counter their protumoral properties has the potential to considerably reduce post-treatment tumor burden. In particular, restoring antitumoral TAM phagocytic activity through anti-CD47 treatment in combination with SOC was predicted to nearly eradicate the tumor. By studying time-varying efficacy with the same half-life as the anti-CD47 antibody Hu5F9-G4, our model predicts that repeated dosing of anti-CD47 provides sustained control of tumor growth. We propose that targeting TAMs by enhancing their antitumoral properties is a highly promising avenue to treat glioblastoma and warrants future clinical development. Together, our results provide proof-of-concept that mechanistic mathematical modeling can uncover the mechanisms driving treatment outcomes and explore the potential of novel treatment strategies for hard-to-treat tumors like glioblastoma.